The growing popularity of hybrids and electric vehicles gives rise to new safety issues in urban environments, as many of the aural cues associated with (combustion) engine noise can be missing. The solution is to intelligently make vehicles noisier. In fact, several countries have established laws that require cars to radiate a minimum level of sound in order to warn other traffic participants of an approaching car.
Some research has been conducted in the field of analyzing and synthesizing sound signals, particularly in the context of speech processing. However, the known methods and algorithms typically require powerful digital signal processors, which are not suitable for the low-cost applications that the automotive industry requires. Synthetic (e.g., combustion engine) sound is not only generated to warn surrounding traffic participants; it may also be reproduced in the interior of the car to provide the driver with acoustic feedback concerning the state of the engine (rotational speed, engine load, throttle position, etc.). However, when synthetic motor sound is reproduced through loudspeakers, the driver will perceive the sound as different from a real combustion engine. There is thus a general need for an improved method for synthesizing motor sound.